La delegación excepcional en la actualidad

5.1 Project Complexity

number of elements Project Complexity Uncertainty uncertainty in goals uncertainty in methods Structural Complexity interdependence of elements

Figure 3: Project complexity (Williams, 1999, p.271)

Projects such as complex adaptive systems are comprised of a great number of elements which have a mutual interaction. Since “complexity can be characterised by two main aspects – quantitative and qualitative” (Geov, 2007, p.1), the quantity complexity aspect in the projects comes from a number of activities and different kinds of activities (for example, preparational activities, operational activities, the ones that happen on paper or in the field, etc.) These activities are mutually intertwined, so it is obvious that there is a great number of connections and dependences which are different as well. For example, in Precedence Diagramming Method (PDM) there are four types of connections: Finish-to-Start (FS), Start-to-Start (SS), Finish-to-Finish (FF), Start-to-Finish (SF). All these relations can have specific lags (such as FS2). Quality complexity aspect is the consequence of quantity aspect when due to many activities and relationships among activities in the project, perception exacerbates and behaviour of the project becomes unpredictable. Apart from the number of activities and number of connections, theirs differences are important for quality aspect of complexity, as well as variability of resources engaged in the project.

When it comes to innovation projects, the biggest problem is weak structuring. There is no previous experience in order to create something new (whether it's a new technology, a new product, or research), and because of that it is hard to know beforehand all tasks that will be undertaken on the project. Frequent changes in the project are usual, as well as the lack of understanding of their consequences.

The butterfly effect, known as an important non-linearity factor, is present in the management project systems. Little changes in certain phases of projects can influence the ultimate outcome. Moreover, if we repeat the same thing in a project, we won’t get the same results every time. It is sometimes hard to connect cause and consequence since nonlinear behaviour is common for big projects. Apart from the great number of events and high degree of interdependence, what also influences this is organizational structure layers in the project and project relationships with other projects (Remington, Zolin, 2011).

The risk and uncertainty of the project are the highest in its initial phase (figure 4), when it is necessary to define the desired goals of the project. There are additional difficulties in risk management of innovation projects, because project risks come from different sources: management, technology and market (Stosic, Isljamovic, & Mihic, 2013).

Project Time

Degree

High

Low

Cost of changes Risk and uncertainty

Having in mind that a great number of factors from the environment affect the project complexity and that projects can be long-lasting, it is necessary to examine the adequacy of originally established goals and redefine them. Projects are adjusted to changeable circumstances in the environment like complex adaptive systems. By changing the project goals, methods used for their achievements are changed.

In the same way that CAS behaviour cannot be predicted in a long period of time (similar to weather forecast), it is not possible to predict future occurrences in the projects whereupon its outcome is uncertain.

5.2 Environment project complexity

If project as a structure is being observed, then its closest environment is made by the people participating in its realization. It is important to consider complexity with project team where the source of complexity comes from the human factor in the first place and then from problem complexity problem which is before the team. The life cycle of a project team consists of several phases and certain patterns of behaviour characteristic to it can be seen. Life cycle of a project team consists of several phases and certain behavioural patterns characteristic for each of them can be spotted. There is the highest complexity during the storm phase, when the situation is far from agreement, precisely as it can be seen on the Stacey matrix, that is to say when the agreement among the team members cannot be achieved. Further during the norming phase and functionality phase projects team members agree, overcome conflicts, and move to the „agreement zone“. All differences between virtual project leadership and leadership in a traditional environment aren’t addressed in the PMBOK Guide (Curlee, Gordon, 2011). According to the PMBOOK Guide (2013), part X3.7 Political and Cultural Awareness, „an effective way to manage this cultural diversity is through getting to know the various team members and the use of good communication planning as part of the overall project plan“ (p. 542). But Curlee and Gordon (2011) considered that this „does not offer any practical recommendations about handling the leadership of a culturally diverse or a geographically dispersed team“ (p. 28). There is a chaotic nature of communication in a virtual project, where lines of communications are tangled and less affected by hierarchy (Curlee, Gordon, 2011), so communication plan must be more flexible and more capable for adjusting the changes. One should be particularly cautious in the case of managing the innovation projects by a virtual project team. Some authors think that virtual projects can exacerbate innovation. Chesbrough and Teece (2002) say that „loose partnerships of companies inevitably produce more conflicts of interest than do centrally managed corporations, and those conflicts can hamper the kind of complex, systematic innovation that creates valuable business breakthroughs“ (p.127).

Stakeholders of a project in accordance with standard BS ISO 21500:2012 are shown on picture 5. All of them together are in mutual interaction which increases project environment complexity. That is reflected on the project itself having in mind that it necessary to fulfil the demands and expectations of all stakeholders and oversight by neglecting any of the sides could lead to project failure.

Project Manager

Project Manager Project Sponsor

Project Management Team

Project Team

Project Organization

Project Governance

Project Steering Committee of Board

Regulatory Bodies

Customers Employees

Project Management Office

Special Interest Groups

Bussiness Partners

Shareholders

Suppliers

Finance Providers

Figure 5: Project stakeholders (BS ISO 21500:2012, p.7)

Even though complexity theory does not advocate the use of any models, just by emphasizing the individuality of each project as well as the impossibility to show complexity by models and ruined picture of reality, there are several attempted models of project management when it comes to complexity.

5.3 Project management models

Depending on project complexity and environment project complexity which have previously been discussed, Jaafari (2003) suggests the following four project management models:

 Ad hoc model – project complexity and environment project complexity are low, the project management has no system approach, nor the occupation of the project manager can be recognized, decisions are made as you go along, the focus is not on long term achievements;

 Bureaucratic model – project complexity and environment project complexity are low to moderate, the approach is characteristic for projects in the public sector, the focus is not on achieving optimal project results as much as it is on administration respect;

 Normative model – it is distinguished by high project complexity and moderate environment project complexity, the modern model is usually described as the model of the best practice;

 Creative-reflective model – there is a high project complexity as well as very high environment project

complexity, projects are not structured, the environment is changeable, study and project managers’ creativity are necessary.

Ad-hoc

Bureaucratic Normative

Creative-Reflective

Low Medium High Very High

Project Complexity Environ me n ta l C o mplexity Lo w Med ium Hi gh Very Hig h

Figure 6: Schematic comparison of four models of project management in terms of complexity (Jaafari,

2003, p.55)

Basically, this classification reflects project management evolution through time in attempt to respond to ascending increase of environment and project complexity (Jaafari, 2003). In this work, the most important is the last crative-reflective model (figure 6) and here is the link with innovation projects.